Electronic image scanners convert an optical image into an electronic form suitable for storage, transmission or printing. Film scanners are used, for example, for X-ray films, developed negative film strips, and slide film (also called reversal film or "chrome" film). In a typical image scanner, light from an image is focused onto linear arrays of photosensors for scanning one line at a time. A two dimensional image is scanned by providing relative movement between the linear sensor arrays and the original image. For gray-scale scanning there may be only a single linear array of photosensors. In general, a color scanner measures the intensity of at least three relatively narrow bands of wavelengths of visible light, for example, bands of red, green and blue. A color scanner may sequentially present multiple bands of wavelengths to a single row of sensor elements by sequentially moving color filters into the light path or by sequentially activating different colored light sources. For higher speed, a color scanner may simultaneously present multiple bands of wavelengths to multiple rows of sensor elements.
FIG. 1 illustrates a typical color scanning assembly for an image scanner or copier using filters. For a film scanner, light is provided by a white light source 101 and is transmitted through a transmissive film 100. An optics assembly 102 focuses light from three separate lines on the film 100, through color filters 104, and onto a three-line photosensor array 106. Typically, the light path is folded by mirrors (not illustrated). An entire image is scanned by providing relative movement between the film 100 and the photosensor array 106 (relative movement in the Y-dimension as illustrated by the arrow 108).
FIG. 2 illustrates an alternative color scanning assembly using a beam splitter. Light is provided by a white light source 201 and is transmitted through a transmissive image 200. An optics assembly 202 focuses light from a single line on film 200, through a beam splitter 204 that splits the light into three relatively narrow bands of wavelengths, each band focused onto a different linear array on a three line photosensor array 206. For additional general background, see for example, K. Douglas Gennetten and Michael J. Steinle, "Designing a Scanner with Color Vision," Hewlett-Packard Journal, August, 1993, pp 52-58.
For the configuration illustrated in FIG. 1, for any one line on the film 100, intensity of one color is measured, then at a later time intensity of a second color is measured, and then at a later time intensity of a third color is measured. Therefore, in the configuration illustrated in FIG. 1, memory is required to buffer intensity measurements for a line on the scanned image until the final measurements are completed for that line. In the configuration illustrated in FIG. 2, for any one line on the film 200, intensity measurements for all colors are made simultaneously, thereby eliminating the requirement for buffer memory for multiple scans of a single line.
For film scanners, the digitized image may be degraded by the presence of artifacts on the surface of the film being scanned, such as dust and fingerprints, or defects in the surface of the film being scanned, such as scratches. This is particularly a problem on smaller film formats such as 35 mm film, since the image area is small. For most uses, the image must be magnified, which magnifies the surface artifacts and defects as well. An operator must be meticulous in storing and handling film in order to minimize these artifacts and defects. Various methods of cleaning or repairing the surface of the film have been used by photo professionals, but they are time consuming and difficult, and only partially successful.
When film is scanned electronically, it is possible to use image processing algorithms to try to reduce or eliminate artifacts and defects in the scanned digital image. However, in general, it is very difficult to distinguish a dust particle or scratch from the desired image. Typically, a human operator must identify the artifact or defect in the digital image to be corrected. This is a time consuming and costly process. Some fully automatic algorithms have been tried, but most of these tend to blur the entire image.
There is a need for automatically uniquely distinguishing surface artifacts and defects from features defined in the image on the film and for automatically correcting identified artifacts in digitized images.